Neurodesign: A Game-Changer in Educational Contexts

In the wake of the COVID-19 pandemic, the importance of assessing students' academic performance has become more critical than ever. With the widespread adoption of remote and hybrid learning models, it is essential to monitor students' progress and identify areas where they may be struggling. Using Artificial Intelligence (AI) to assess students' performance can help prevent the dispersion of educational outcomes that may result from the pandemic. By leveraging advanced techniques such as Deep Learning and Computer Vision, educators can extract features from students' data, including their facial expressions and sentiment analysis, to gain insights into their learning progress and emotional wellbeing. Through our proposed approach that combines Facial Expression Recognition (FER) and Sentiment Analysis techniques, we can detect stress periods and improve students' academic performance. This can enable educators to identify students who may be struggling with the transition to remote learning or facing other challenges and provide them with the support they need to succeed. Overall, our research highlights how AI-based student performance assessment can play a critical role in ensuring that students' educational outcomes are not adversely affected by the pandemic. By monitoring students' progress and providing targeted interventions to support their learning, educators can help prevent the dispersion of educational outcomes and ensure that all students receive the education they deserve